Job Matching Agent: ASU Career Services
The Arizona State University Artificial Intelligence Cloud Innovation Center (ASU CIC), powered by Amazon Web Services (AWS), collaborated with Arizona State University (ASU) Career Services department to develop an AI-powered job-matching assistant that personalizes how students and alumni discover employment opportunities.
This initiative focuses on improving how job seekers connect to relevant jobs, internships, and career pathways—streamlining searches and reducing time spent navigating multiple systems.
Problem
Each semester, thousands of ASU students and graduates search for positions across multitudes of platforms. Despite ASU Career Services offering extensive digital resources, many users still struggle to find roles tailored to their goals or fields of study.
Manual searches, limited keyword filters, and scattered job databases often result in missed opportunities and duplicated effort. Career Services sought a centralized, intelligent solution capable of understanding student skills and matching them with relevant openings—reducing friction and saving time for both students and advisors.
Student Spotlight
The AI CIC is powered by ASU student workers. The following students collaborated with AWS mentors to design and develop this solution:
Role: UI/UX Designer | Connect with Lahari on LinkedIn
Experience: It was a pleasure getting to be the UI/UX designer on this project, solving a problem that I can very much relate to as a 4th year student at ASU- searching for jobs! The current experience has made job searching a very difficult task for most students. The user interface is overwhelming, offers generic job recommendations, and limited profile customization. The Agentic Job Search Chatbot offers a seamless experience where users can upload their resume with autofill capability, serving three key purposes: Part-Time Job Search, Full-Time Job Search, and Career Exploration.The user interface incorporates ASU branding elements to establish trust and functions as a conversational chatbot rather than a Q & A chatbot by remembering previous interactions. The chatbot also personalizes job recommendations based on location preferences, individual needs, and what job setting they prefer, allowing students to search for jobs through natural conversation instead of clicking many buttons. The one feature that I’m proud of implementing is the resume-autofill feature I added in the user profile page and the feature where the user can select which method they would prefer to receive job notifications in the future. I’m excited about the prospect of other universities adopting our solution to help with the student job search process as well!
Role: Cloud Developer | Connect with Aryan on LinkedIn
Experience: Working on Agentic Job Search has been one of the most exciting and fulfilling experiences of my journey. Built by students, for students, the platform connects people to opportunities that truly fit by understanding their skills, projects, experiences, and interests, and matching them with the roles, products, and missions of real companies. What made this project so special was knowing we were creating something that doesn’t just help students find jobs, but helps them discover why a role fits them and even guides them through their career questions along the way. The part I loved most was developing AI agents that seamlessly orchestrated with one another behind the scenes to deliver exactly the insights each student is looking for, making the entire experience feel personal, intelligent, and human-like.
Role: Cloud Developer | Connect with Aarav on LinkedIn
Experience: Working on the Agentic Job Search project was one of my most exciting and meaningful experiences at the CIC. This AI platform was designed to connect people with opportunities that truly fit, not just based on keywords or titles, but by understanding their skills, experiences, and interests, and matching them with roles and missions that align with their needs. It made the process that much more personalized and efficient. I especially enjoyed working on building the resume parser using AWS Lambda, developing the AgentCore agents for career exploration and job search, and also setting up the RAG pipeline that powers personalized, intelligent recommendations. This meant working with the newest tools like Amazon Bedrock Agentcore and S3 Vector Stores to create a system that could truly understand and serve each student’s needs. It was an incredible learning opportunity as I got a deep dive into cloud architecture, AI agent orchestration, and RAG systems, and saw firsthand how all these technologies can come together to create something that is genuinely impactful.
Approach
The ASU CIC team is developing a prototype that uses AI-driven matching algorithms to connect students with relevant job postings from Handshake and other online sources. The web-based interface allows students to upload résumés, set career preferences and instantly view personalized recommendations ranked by skill alignment and location fit. Unlike traditional search tools that rely on static inputs and outputs, the interactive chat-style design encourages a conversational back-and-forth experience — an approach students tend to prefer because it keeps them more engaged in their career exploration.
The solution uses several key Amazon Web Services products to ensure scalability, speed and security. Amazon Bedrock provides generative AI capabilities to interpret résumés and extract relevant skills. AWS Lambda automates back-end logic for data processing and job-matching operations. Amazon S3 securely stores anonymized data sets and processed job information. Amazon API Gateway manages secure communication between the user interface and back-end functions. Amazon DynamoDB maintains structured records of user preferences and job data for quick retrieval. AWS Amplify hosts the web application, enabling fast iteration and deployment.
Together, these services create a reliable, serverless environment that delivers job recommendations within seconds — helping Career Services scale personalized career guidance to thousands of users.
Industry Impact
This project represents a major step forward in how higher-education institutions support career readiness through artificial intelligence. Designed as an open-source product, the tool can be integrated with existing job search platforms to make recommendations more curated and adaptable to different systems. By automating résumé analysis and job matching, ASU Career Services can devote more time to personalized advising, employer engagement and professional development programming.
The AI assistant will also enable the university to gather anonymous insights on job trends and skills demand, allowing advisors and administrators to align curricula and workshops with evolving labor-market needs.
“Partnering with the Cloud Innovation Center has been an incredible opportunity to explore how AI can transform the career search experience for students and alumni. Through this collaboration, we gained a deeper understanding of how generative AI can analyze skills, interests, and labor-market trends to make job discovery more intuitive and equitable. The prototype directly supports our mission to reduce barriers to opportunity and provide personalized, scalable career guidance across the ASU community.”
ASU Career Services Team
Wider Application
The framework designed for ASU Career Services can be applied far beyond the university setting.
- Universities can replicate this architecture to connect students and alumni to internships, fellowships, and research positions.
- Workforce-development agencies can match job seekers with local employment programs using AI-driven recommendations.
- Corporate HR teams can adapt the system to analyze internal career-mobility opportunities and training pathways.
By combining advanced language models, secure cloud infrastructure, and user-friendly design, this solution demonstrates how institutions can modernize career support, strengthen data insights, and foster equitable access to employment.
Next Steps
The next step is to work with the ASU Enterprise Technology team to integrate the prototype into existing ASU tools and assess its impact on engagement and career outcomes. They plan to collaborate with additional university partners to refine data inputs, expand the range of job sources, and evaluate how the tool complements our career-readiness curriculum. Beyond technical development, this project has sparked new ideas about how AI can amplify human advising, streamline systems, and inform data-driven decisions that enhance student success.
About the ASU CIC
The ASU Artificial Intelligence Cloud Innovation Center (AI CIC), powered by AWS is a no-cost design thinking and rapid prototyping shop dedicated to bridging the digital divide and driving innovation in the nonprofit, healthcare, education, and government sectors.
Our expert team harnesses Amazon’s pioneering approach to dive deep into high-priority pain points, meticulously define challenges, and craft strategic solutions. We collaborate with AWS solutions architects and talented student workers to develop tailored prototypes showcasing how advanced technology can tackle a wide range of operational and mission-related challenges.
Discover how we use technology to drive innovation. Visit our website at ASU AI CIC or contact us directly at [email protected].
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